#include "libavformat/avio.h"
#include "libavutil/opt.h"
#include "avfilter.h"
-#include "dnn_interface.h"
+#include "dnn_filter_common.h"
#include "formats.h"
#include "internal.h"
typedef struct DRContext {
const AVClass *class;
-
+ DnnContext dnnctx;
int filter_type;
- char *model_filename;
- DNNBackendType backend_type;
- DNNModule *dnn_module;
- DNNModel *model;
- DNNData input;
- DNNData output;
} DRContext;
-#define CLIP(x, min, max) (x < min ? min : (x > max ? max : x))
#define OFFSET(x) offsetof(DRContext, x)
#define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
static const AVOption derain_options[] = {
{ "filter_type", "filter type(derain/dehaze)", OFFSET(filter_type), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, 1, FLAGS, "type" },
{ "derain", "derain filter flag", 0, AV_OPT_TYPE_CONST, { .i64 = 0 }, 0, 0, FLAGS, "type" },
{ "dehaze", "dehaze filter flag", 0, AV_OPT_TYPE_CONST, { .i64 = 1 }, 0, 0, FLAGS, "type" },
- { "dnn_backend", "DNN backend", OFFSET(backend_type), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, 1, FLAGS, "backend" },
+ { "dnn_backend", "DNN backend", OFFSET(dnnctx.backend_type), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, 1, FLAGS, "backend" },
{ "native", "native backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 0 }, 0, 0, FLAGS, "backend" },
#if (CONFIG_LIBTENSORFLOW == 1)
{ "tensorflow", "tensorflow backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 1 }, 0, 0, FLAGS, "backend" },
#endif
- { "model", "path to model file", OFFSET(model_filename), AV_OPT_TYPE_STRING, { .str = NULL }, 0, 0, FLAGS },
+ { "model", "path to model file", OFFSET(dnnctx.model_filename), AV_OPT_TYPE_STRING, { .str = NULL }, 0, 0, FLAGS },
+ { "input", "input name of the model", OFFSET(dnnctx.model_inputname), AV_OPT_TYPE_STRING, { .str = "x" }, 0, 0, FLAGS },
+ { "output", "output name of the model", OFFSET(dnnctx.model_outputname), AV_OPT_TYPE_STRING, { .str = "y" }, 0, 0, FLAGS },
{ NULL }
};
return ff_set_common_formats(ctx, formats);
}
-static int config_inputs(AVFilterLink *inlink)
-{
- AVFilterContext *ctx = inlink->dst;
- DRContext *dr_context = ctx->priv;
- const char *model_output_name = "y";
- DNNReturnType result;
-
- dr_context->input.width = inlink->w;
- dr_context->input.height = inlink->h;
- dr_context->input.channels = 3;
-
- result = (dr_context->model->set_input_output)(dr_context->model->model, &dr_context->input, "x", &model_output_name, 1);
- if (result != DNN_SUCCESS) {
- av_log(ctx, AV_LOG_ERROR, "could not set input and output for the model\n");
- return AVERROR(EIO);
- }
-
- return 0;
-}
-
static int filter_frame(AVFilterLink *inlink, AVFrame *in)
{
AVFilterContext *ctx = inlink->dst;
AVFilterLink *outlink = ctx->outputs[0];
DRContext *dr_context = ctx->priv;
DNNReturnType dnn_result;
+ AVFrame *out;
- AVFrame *out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
+ out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
if (!out) {
av_log(ctx, AV_LOG_ERROR, "could not allocate memory for output frame\n");
av_frame_free(&in);
return AVERROR(ENOMEM);
}
-
av_frame_copy_props(out, in);
- for (int i = 0; i < in->height; i++){
- for(int j = 0; j < in->width * 3; j++){
- int k = i * in->linesize[0] + j;
- int t = i * in->width * 3 + j;
- ((float *)dr_context->input.data)[t] = in->data[0][k] / 255.0;
- }
- }
-
- dnn_result = (dr_context->dnn_module->execute_model)(dr_context->model, &dr_context->output, 1);
+ dnn_result = ff_dnn_execute_model(&dr_context->dnnctx, in, out);
if (dnn_result != DNN_SUCCESS){
av_log(ctx, AV_LOG_ERROR, "failed to execute model\n");
+ av_frame_free(&in);
return AVERROR(EIO);
}
- out->height = dr_context->output.height;
- out->width = dr_context->output.width;
- outlink->h = dr_context->output.height;
- outlink->w = dr_context->output.width;
-
- for (int i = 0; i < out->height; i++){
- for(int j = 0; j < out->width * 3; j++){
- int k = i * out->linesize[0] + j;
- int t = i * out->width * 3 + j;
- out->data[0][k] = CLIP((int)((((float *)dr_context->output.data)[t]) * 255), 0, 255);
- }
- }
-
av_frame_free(&in);
return ff_filter_frame(outlink, out);
static av_cold int init(AVFilterContext *ctx)
{
DRContext *dr_context = ctx->priv;
-
- dr_context->input.dt = DNN_FLOAT;
- dr_context->dnn_module = ff_get_dnn_module(dr_context->backend_type);
- if (!dr_context->dnn_module) {
- av_log(ctx, AV_LOG_ERROR, "could not create DNN module for requested backend\n");
- return AVERROR(ENOMEM);
- }
- if (!dr_context->model_filename) {
- av_log(ctx, AV_LOG_ERROR, "model file for network is not specified\n");
- return AVERROR(EINVAL);
- }
- if (!dr_context->dnn_module->load_model) {
- av_log(ctx, AV_LOG_ERROR, "load_model for network is not specified\n");
- return AVERROR(EINVAL);
- }
-
- dr_context->model = (dr_context->dnn_module->load_model)(dr_context->model_filename, NULL);
- if (!dr_context->model) {
- av_log(ctx, AV_LOG_ERROR, "could not load DNN model\n");
- return AVERROR(EINVAL);
- }
-
- return 0;
+ return ff_dnn_init(&dr_context->dnnctx, DFT_PROCESS_FRAME, ctx);
}
static av_cold void uninit(AVFilterContext *ctx)
{
DRContext *dr_context = ctx->priv;
-
- if (dr_context->dnn_module) {
- (dr_context->dnn_module->free_model)(&dr_context->model);
- av_freep(&dr_context->dnn_module);
- }
+ ff_dnn_uninit(&dr_context->dnnctx);
}
static const AVFilterPad derain_inputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
- .config_props = config_inputs,
.filter_frame = filter_frame,
},
{ NULL }
{ NULL }
};
-AVFilter ff_vf_derain = {
+const AVFilter ff_vf_derain = {
.name = "derain",
.description = NULL_IF_CONFIG_SMALL("Apply derain filter to the input."),
.priv_size = sizeof(DRContext),
projects / ffmpeg / blobdiff